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1. 发明申请

WO2019236386A1 COMPUTING NODE FAILURE AND HEALTH PREDICTION FOR CLOUD-BASED DATA CENTER 审中-公开
公开(公告)号：WO2019236386A1
公开(公告)日：2019-12-12
申请号：PCT/US2019/034769
申请日：2019-05-31
申请人： MICROSOFT TECHNOLOGY LICENSING, LLC
发明人： CHINTALAPATI, Murali M. , HSIEH, Ken , WU, Youjiang , YAO, Randolph , LIN, Qingwei , DANG, Yingnong
IPC分类号： G06F9/50
摘要： A system may include a node historical state data store having historical node state data, including a metric that represents a health status or an attribute of a node during a period of time prior to a node failure. A node failure prediction algorithm creation platform may generate a machine learning trained node failure prediction algorithm. An active node data store may contain information about computing nodes in a cloud computing environment, including, for each node, a metric that represents a health status or an attribute of that node over time. A virtual machine assignment platform may then execute the node failure prediction algorithm to calculate a node failure probability score for each computing node based on the information in the active node data store. As a result, a virtual machine may be assigned to a selected computing node based at least in part on node failure probability scores.

2. 发明申请

WO2021216270A1 DIAGNOSING AND MITIGATING MEMORY LEAK IN COMPUTING NODES 审中-公开
公开(公告)号：WO2021216270A1
公开(公告)日：2021-10-28
申请号：PCT/US2021/025695
申请日：2021-04-05
申请人： MICROSOFT TECHNOLOGY LICENSING, LLC
发明人： CHEN, Cong , YANG, Xinsheng , DANG, Yingnong , QIN, Si
IPC分类号： H04L12/24 , H04L12/26
摘要： The present disclosure relates to systems, methods, and computer readable media for diagnosing and mitigating memory impact events, such as memory leaks, high memory usage, or other memory issues causing a host node from performing as expected on a cloud computing system. The systems described herein involve receiving locally generated memory usage data from a plurality of host nodes. The systems described herein may aggregate the memory usage data and determine a memory impact diagnosis based on a subset of the aggregated memory usage data. The systems described herein may further apply a mitigation model for mitigating the memory impact event. The systems described herein provide an end-to-end solution for diagnosing and mitigating a variety of memory issues using a dynamic and scalable system that reduces a negative impact of memory leaks and other memory issues on a cloud computing system.

3. 发明申请

WO2016000158A1 CODE RECOMMENDATION 审中-公开
标题翻译：代码建议
公开(公告)号：WO2016000158A1
公开(公告)日：2016-01-07
申请号：PCT/CN2014/081228
申请日：2014-06-30
申请人： MICROSOFT TECHNOLOGY LICENSING, LLC , DANG, Yingnong
发明人： DANG, Yingnong , ZHONG, Chenglin , WU, Qian , YIN, Han , SCHWARZ, Niko , ZHANG, Dongmei
IPC分类号： G06F9/44
CPC分类号： G06F8/36 , G06F8/20 , G06F8/30 , G06F8/33
摘要： A method generally relates to code recommendation. In the method, code snippets (220 1 , 220 2 , …220 n ) may be extracted using an invocation-centered code slicing process and then grouped according to the method usages. For each method usage, a representative code snippet may be selected and stored in the knowledge base (210) in association with metadata (230 1 , 230 2 , …230 n ). The programming context may be obtained and used to query the knowledge base (210) to retrieve one or more code snippets for recommendation. The recommended code snippets may be ranked to improve the utility and user friendliness, and the metadata (230 1 , 230 2 , …230 n ) may be used to provide variation points and possibly other auxiliary information to improve the operation efficiency and user experience.
摘要翻译：方法一般涉及代码推荐。在该方法中，可以使用以调用为中心的代码分割处理来提取代码片段（220 1，220 2，... 220 n），然后根据方法用法进行分组。对于每种方法使用，可以与元数据（230 1，230 2，... 230 n）相关联地选择代表性代码片段并将其存储在知识库（210）中。可以获得编程上下文并用于查询知识库（210）以检索用于推荐的一个或多个代码片段。推荐的代码片段可以被排名以提高效用和用户友好性，并且可以使用元数据（230 1，230 2，... 230 n）来提供变化点和可能的其他辅助信息，以提高操作效率和用户体验。

4. 发明申请

WO2015113301A1 AUTOMATIC INSIGHTS FOR SPREADSHEETS 审中-公开
标题翻译：自动分析报告
公开(公告)号：WO2015113301A1
公开(公告)日：2015-08-06
申请号：PCT/CN2014/071837
申请日：2014-01-30
申请人： MICROSOFT TECHNOLOGY LICENSING, LLC , DANG, Yingnong , LIU, Shusen , LIANG, Xiao , ZHANG, Haidong , SUN, Jim , ZHANG, Dongmei , RUBLE, Scott
发明人： DANG, Yingnong , LIU, Shusen , LIANG, Xiao , ZHANG, Haidong , SUN, Jim , ZHANG, Dongmei , RUBLE, Scott
IPC分类号： G06F17/30
CPC分类号： G06F17/246 , G06F17/28 , G06Q10/063 , G06Q30/0201
摘要： Automatically identifying insights from a dataset and presenting the insights graphically and in natural language text ranked by importance is provided. Different data types and structures in the dataset are automatic recognized and matched with a corresponding specific analysis type. The data is analyzed according to the determined corresponding analysis types, and insights from the analysis are automatically identified. The insights within a given insight type and between insight types are ranked and presented in order of importance in automatically generate charts that visually describe each insight and in natural language text that describes each insight in such a way that it may be understandable to a general audience who may not have a familiarity with statistics.
摘要翻译：自动识别数据集中的见解，并以图形和自然语言文本以重要性排列呈现洞察力。数据集中的不同数据类型和结构将自动识别并与相应的特定分析类型相匹配。根据确定的相应分析类型分析数据，并自动识别分析的见解。给定洞察类型和洞察类型之间的洞察力按照重要性的顺序排列并显示，以自动生成图表，以视觉描述每个洞察力和自然语言文本，描述每个洞察力，使其对一般观众可能是可以理解的谁可能不熟悉统计资料。

5. 发明申请

WO2018018575A1 DETECTION OF COMPUTING RESOURCE LEAKAGE IN CLOUD COMPUTING ARCHITECTURES 审中-公开
标题翻译：云计算架构中计算资源泄漏的检测
公开(公告)号：WO2018018575A1
公开(公告)日：2018-02-01
申请号：PCT/CN2016/092215
申请日：2016-07-29
申请人： MICROSOFT TECHNOLOGY LICENSING, LLC , YANG, Xinsheng , DANG, Yingnong , DING, Justin
发明人： YANG, Xinsheng , DANG, Yingnong , DING, Justin
IPC分类号： G06F11/30
摘要： Techniques and systems for detecting leakage of computing resources in cloud computing architectures are described. In some implementations, first data may be obtained that indicates usage of a computing resource, such as non-volatile memory, volatile memory, processor cycles, or network resources, by a group of computing devices included in a cloud computing architecture. The first data may be used to determine reference data that may include a distribution of values of usage of the computing resource by the group of computing devices. Second data may also be collected that indicates usage of the computing resource by the group of computing devices during a subsequent time frame. The second data may be evaluated against the reference data to determine whether one or more conditions indicating a leak of the computing resource are satisfied.
摘要翻译：描述了用于检测云计算体系结构中的计算资源泄漏的技术和系统。在一些实现中，可以通过包括在云计算体系结构中的一组计算设备来获得指示诸如非易失性存储器，易失性存储器，处理器周期或网络资源的计算资源的使用的第一数据。第一数据可以用于确定参考数据，该参考数据可以包括该组计算设备对计算资源的使用值的分布。还可以收集第二数据，其指示在后续时间帧期间该组计算设备对计算资源的使用。可以针对参考数据评估第二数据以确定是否满足指示计算资源泄漏的一个或多个条件。

6. 发明公开

EP3161618A1 CODE RECOMMENDATION 审中-公开
标题翻译：代码推荐
公开(公告)号：EP3161618A1
公开(公告)日：2017-05-03
申请号：EP14896433.1
申请日：2014-06-30
申请人： Microsoft Technology Licensing, LLC
发明人： DANG, Yingnong , ZHONG, Chenglin , WU, Qian , YIN, Han , SCHWARZ, Niko , ZHANG, Dongmei
IPC分类号： G06F9/44
CPC分类号： G06F8/36 , G06F8/20 , G06F8/30 , G06F8/33
摘要： A method generally relates to code recommendation. In the method, code snippets (220
1 , 220
2 , …220
n ) may be extracted using an invocation-centered code slicing process and then grouped according to the method usages. For each method usage, a representative code snippet may be selected and stored in the knowledge base (210) in association with metadata (230
1 , 230
2 , …230
n ). The programming context may be obtained and used to query the knowledge base (210) to retrieve one or more code snippets for recommendation. The recommended code snippets may be ranked to improve the utility and user friendliness, and the metadata (230
1 , 230
2 , …230
n ) may be used to provide variation points and possibly other auxiliary information to improve the operation efficiency and user experience.
摘要翻译：本公开总体上涉及代码推荐。在一个实施例中，可以使用以调用为中心的代码分片过程来提取代码片段，然后根据该方法使用来分组代码片段。对于每种方法使用，可以选择代表性代码片段并将其与元数据相关联地存储在知识库中。在操作中，可以获得编程上下文并将其用于查询知识库以检索用于推荐的一个或多个代码片段。在一个实施例中，可以对推荐的代码片段进行排序以提高效用和用户友好度，并且可以使用元数据来提供变化点和可能的其他辅助信息以提高操作效率和用户体验。

7. 发明公开

EP3008633A1 FAST GROUPING OF TIME SERIES 审中-公开
标题翻译：时间序列的快速分组
公开(公告)号：EP3008633A1
公开(公告)日：2016-04-20
申请号：EP13887005.0
申请日：2013-06-14
申请人： Microsoft Technology Licensing, LLC
发明人： DANG, Yingnong , WANG, Qiang , ZHAO, Qianchuan , WANG, Shulei , DING, Rui, Justin , FU, Qiang , ZHANG, Dongmei
IPC分类号： G06F17/30
CPC分类号： G06F17/30598 , G06F17/18 , G06F17/3033 , G06F17/30943 , G06K9/0055 , G06K9/6222
摘要： In some examples, a time-series data set can be analyzed and grouped in a fast and efficient manner. For instance, fast grouping of multiple time-series into clusters can be implemented through data reduction, determining cluster population, and fast matching by locality sensitive hashing. In some situations, a user can select a level of granularity for grouping time-series into clusters, which can involve trade-offs between the number of clusters and the maximum distance between two time-series in a cluster.
摘要翻译：在一些示例中，时间序列数据集可以以快速和有效的方式进行分析和分组。例如，可以通过数据缩减，确定聚类人口以及通过局部敏感散列进行快速匹配来实现将多个时间序列快速分组成簇。在某些情况下，用户可以选择用于将时间序列分组为簇的粒度级别，这可能涉及群集数量与群集中两个时间序列之间的最大距离之间的权衡。

8. 发明公开

EP3803593A1 COMPUTING NODE FAILURE AND HEALTH PREDICTION FOR CLOUD-BASED DATA CENTER 审中-公开
公开(公告)号：EP3803593A1
公开(公告)日：2021-04-14
申请号：EP19736536.4
申请日：2019-05-31
申请人： Microsoft Technology Licensing, LLC
发明人： CHINTALAPATI, Murali M. , HSIEH, Ken , WU, Youjiang , YAO, Randolph , LIN, Qingwei , DANG, Yingnong
IPC分类号： G06F9/50

9. 发明公开

EP4140100A1 DIAGNOSING AND MITIGATING MEMORY LEAK IN COMPUTING NODES 审中-实审
公开(公告)号：EP4140100A1
公开(公告)日：2023-03-01
申请号：EP21721725.6
申请日：2021-04-05
申请人： Microsoft Technology Licensing, LLC
发明人： CHEN, Cong , YANG, Xinsheng , DANG, Yingnong , QIN, Si
IPC分类号： H04L12/24 , H04L12/26

10. 发明公开

EP3100178A1 AUTOMATIC INSIGHTS FOR SPREADSHEETS 审中-公开
标题翻译：自动眼识TABLES
公开(公告)号：EP3100178A1
公开(公告)日：2016-12-07
申请号：EP14881128.4
申请日：2014-01-30
申请人： Microsoft Technology Licensing, LLC
发明人： DANG, Yingnong , LIU, Shusen , LIANG, Xiao , ZHANG, Haidong , SUN, Jim , ZHANG, Dongmei , RUBLE, Scott
IPC分类号： G06F17/30 , G06F17/24
CPC分类号： G06F17/246 , G06F17/28 , G06Q10/063 , G06Q30/0201
摘要： Automatically identifying insights from a dataset and presenting the insights graphically and in natural language text ranked by importance is provided. Different data types and structures in the dataset are automatic recognized and matched with a corresponding specific analysis type. The data is analyzed according to the determined corresponding analysis types, and insights from the analysis are automatically identified. The insights within a given insight type and between insight types are ranked and presented in order of importance in automatically generate charts that visually describe each insight and in natural language text that describes each insight in such a way that it may be understandable to a general audience who may not have a familiarity with statistics.

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